Maintaining data storage in accordance with an access metric

ABSTRACT

A method includes identifying a data object for retrieval. The data object is encoded in accordance with first encoded parameters and stored as a plurality of sets of encoded data slices in a set of storage units. The method further includes determining whether an access metric regarding the data object exceeds an access threshold. When the access metric is equal to or exceeds the access threshold, the data object is further encoded in accordance with second encoding parameters and stored as a second plurality of sets of encoded data slices in a second set of storage units. The method further includes issuing retrieval requests to the second set of storage units regarding the second plurality of encoded data slices in accordance with a read threshold of the second encoding parameters. The method further includes recovering the data object from the second plurality of encoded data slices.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §120 as a continuation of U.S. Utility application Ser. No.14/680,459, entitled “MAINTAINING DATA STORAGE IN ACCORDANCE WITH ANACCESS METRIC”, filed Apr. 7, 2015, which claims priority pursuant to 35U.S.C. §119(e) to U.S. Provisional Application No. 62/008,207, entitled“PRIORITIZING TASKS IN A STORAGE UNIT”, filed Jun. 5, 2014, both ofwhich are hereby incorporated herein by reference in their entirety andmade part of the present U.S. Utility Patent Application for allpurposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT—NOTAPPLICABLE INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACTDISC—NOT APPLICABLE BACKGROUND OF THE INVENTION

Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc., on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of establishing anoperation execution schedule in accordance the present invention.

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 41B is a flowchart illustrating an example of reproducing datautilizing local redundancy in accordance the present invention;

FIGS. 42A-C are a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 42D is a flowchart illustrating an example of maintaining datastorage in accordance with an access metric in accordance the presentinvention;

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 43B is a flowchart illustrating an example of balancing loading ofstorage resources in accordance the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 44B is a flowchart illustrating an example of rebuilding an encodeddata slice in accordance the present invention;

FIGS. 45A-C are a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 45D is a flowchart illustrating an example of verifying a statuslevel of stored encoded data slices in a dispersed storage network inaccordance the present invention;

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 46B is a flowchart illustrating an example of updating captureddata in accordance the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 47B is a flowchart illustrating an example of associating storageof data and auxiliary data in a dispersed storage network in accordancethe present invention;

FIG. 48A is a diagram of an embodiment of a backup file system structurein accordance with the present invention; and

FIG. 48B is a flowchart illustrating an example of performing anefficient backup of a group of data files using a dispersed storagenetwork in accordance the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interface 30supports a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1−n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1−n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1−n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1−n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the grouping selector modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phrase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith grouping selector information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selector module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selector module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selector module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selector module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selector module 114 creates a fourth slice grouping for DSTexecution unit #4, which includes fourth encoded slices of each of thesets of encoded slices. As such, the fourth DST execution unit receivesencoded data slices corresponding to first error encoding information(e.g., encoded data slices of error coding (EC) data). The groupingselector module 114 further creates a fifth slice grouping for DSTexecution unit #5, which includes fifth encoded slices of each of thesets of encoded slices. As such, the fifth DST execution unit receivesencoded data slices corresponding to second error encoding information.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1−x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 in thememory 88. For example, when the partial task 98 includes a retrievalrequest, the controller 86 outputs the memory control 174 to the memory88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieved slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1−x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selector module organizes the sets of encoded dataslices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selector module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selector module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4—translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6—determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7—determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases 288. The translated data 282 istranslated back 308 (e.g., sub-task 1_4) into the language of theoriginal data to produce re-translated data 284. These two tasks aredependent on the translate task (e.g., task 1_3) and thus must beordered after the translation task, which may be in a pipelined orderingor a serial ordering. The re-translated data 284 is then compared 310with the original data 92 to find words and/or phrases that did nottranslate (one way and/or the other) properly to produce a list ofincorrectly translated words 294. As such, the comparing task (e.g.,sub-task 1_5) 310 is ordered after the translation 306 andre-translation tasks 308 (e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done by the DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words). Task 1_3 (e.g., translate) includes taskexecution information as being non-ordered (i.e., is independent),having DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 translate datapartitions 2_1 through 2_4 and having DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 translate data partitions 2_5 through 2_z to producetask 1_3 intermediate results (R1-3, which is the translated data). Inthis example, the data partitions are grouped, where different sets ofDT execution modules perform a distributed sub-task (or task) on eachdata partition group, which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3_z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4_z to produce task 1_5 intermediate results (R1-5,which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases). Task 3_2 (e.g., findspecific translated words and/or phrases) is ordered after task 1_3(e.g., translate) is to be performed on partitions R1-3_1 through R1-3_zby DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2. For instance, DTexecution modules 1_2, 2_2, 3_2, 4_2, and 5_2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_1 through R1-3_z) to produce task 3_2 intermediate results (R3-2,which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3 y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3 z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4 z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5 z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., l′ through “zth”) of a list ofincorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6 z). Foreach partition of the sixth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions. As indicated in the DST allocation information of FIG. 32,DST execution unit 7 is assigned to process the first through “zth”partial results of task 2 to produce task 2 intermediate result (R2),which is a list of specific words and/or phrases found in the data. Theprocessing module of DST execution 7 is engaged to aggregate the firstthrough “zth” partial results of specific words and/or phrases toproduce the task 2 intermediate result. The processing module stores thetask 2 intermediate result as non-DS error encoded data in thescratchpad memory or in another section of memory of DST execution unit7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabyte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) that includes a set of distributed storage andtask (DST) execution units 1−n and the network 24 of FIG. 1.Alternatively, the DSN may include any number of DST execution units.Each DST execution unit may be implemented utilizing the DST executionunit 36 of FIG. 1. Each DST execution unit includes the processingmodule 84 of FIG. 3, the memory 88 of FIG. 3, the DST client module 34of FIG. 3, and the distributed task (DT) execution module 90 of FIG. 3.One or more portions of the memory 88 are utilized for storage of amaintenance queue 350, a non-maintenance queue 352, and encoded dataslices 354. The DSN functions to establish an operation executionschedule for instructions for execution by the set of DST executionunits.

In an example of operation, the processing module 84 of each DSTexecution unit identifies pending maintenance operations. Suchmaintenance operations includes one or more of rebuilding encoded dataslices associated with storage errors, migrating encoded data slices,transferring encoded data slices copying encoded data slices, and theDST client module 34 encoding encoded data slices to produce localredundancy slices. The identifying includes accessing the maintenancequeue 350 of the memory 88, where the maintenance queue 350 includesinstructions for execution associated with the maintenance operations.

Having identified the pending maintenance operations, the processingmodule 84 identifies pending non-maintenance operations. Suchnon-maintenance operations includes one or more of storing encoded dataslices, retrieving encoded data slices, and the DT execution module 90executing the partial tasks to produce partial results. The identifyingincludes accessing the non-maintenance queue 352 of the memory 88, wherethe non-maintenance queue 352 includes instructions for executionassociated with the non-maintenance operations.

Having identified the pending non-maintenance operations, for a futuretimeframe, the processing module 84 determines a resource availabilitylevel to support execution of at least some of the pending maintenanceand non-maintenance operations. For example, the processing moduleobtains, via the network 24, resource allocation information 356 fromtwo or more of the DST execution units of the set of DST executionunits. The resource allocation information 356 includes one or more ofavailable resources, a current operation execution schedule, a list ofpending operations, and an estimate of required resources associatedwith execution of the pending operations.

Having determined the resource availability level, the processing module84 estimates a required resource level to execute at least some of thepending maintenance operations. For example, the processing moduleestimates the required resource level for each type of pending operationbased on one or more of historical execution records, an operation type,a predetermination, performing a test, and interpreting test results.Having estimated the required resource level to execute the at leastsome of the pending maintenance operations, the processing module 84estimates a required resource level to execute at least some of thepending non-maintenance operations.

Having estimated the required resource levels, the processing module 84determines a balance factor to balance utilization of resources betweenthe execution of pending maintenance operations and pendingnon-maintenance operations. The determining may be based on one or moreof historical operation execution records, a priority level for thepending non-maintenance operations, and a number of pending maintenanceoperations. For example, the processing module 84 allocates a portion ofan overall resource (e.g., time, number of modules) budget to executionof instructions associated with the maintenance queue in thenon-maintenance queue. For instance, the processing module 84 allocates15% of available resources for maintenance operations and a remaining85% of available resources for non-maintenance operations.

Having determined the balance factor, the processing module 84coordinates determination of required timing of pending operationexecution with one or more other DST execution units of the set of DSTexecution units. For example, the processing module 84 coordinatesproducing of partial results for a common partial task substantially thesame time. As another example, the processing module 84 coordinatesretrieval of the set of encoded data slices 354 at substantially thesame time. As yet another example, the processing module 84 coordinatesscanning of the common DSN address range for storage errors by certaintimeframe. Having coordinated the required timing, the processing module84 updates an operation execution schedule based on one or more of theresource availability level, the required resource levels, the balancefactor, and the required timing. For example, the processing module 84coordinates with the at least one other DST execution unit to arrive atsubstantially similar time frames for initiation of execution of pendingoperations.

FIG. 40B is a flowchart illustrating an example of establishing anoperation execution schedule in accordance the present invention. Themethod begins or continues at step 358 where a processing module (e.g.,of a distributed storage and task (DST) execution unit) identifiespending operations. The identifying includes at least one of receivingan operation request, interpreting a list of pending operations, andsearching for pending operations. The identifying may further includeidentifying a type of pending operation, e.g., maintenance, andnon-maintenance.

The method continues at step 360 where the processing module determinesrequired resource levels to execute at least some of the pendingoperations. The method continues at step 362 where the processing moduledetermines the resource availability level support execution of some ofthe pending operations. The method continues at step 364 where theprocessing module determines a balance factor between two or more typesof the pending operations. The determining includes at least one ofinterpreting a goal, interpreting historical operation executionrecords, interpreting a priority level for an operation, identifying anumber of pending maintenance operations, and identifying a currentbalance factor.

The method continues at step 366 where the processing module coordinatesdetermining of required timing of the execution of the at least some ofthe pending operations with one or more other operation executionentities. The coordinating includes one or more of identifying candidateoperations requiring coordination, sending identifiers of the candidateoperations to the one or more other operation execution entities (e.g.,other storage units), estimating the required timing of the execution,and modifying the estimate of the required timing of execution based onreceived resource allocation information.

The method continues at step 368 where the processing module updates anoperation execution schedule based on one or more of the requiredresource levels, the resource availability level, the balance factor,and the required timing of the execution. For example, the processingmodule modifies a previous operation scheduled to achieve execution ofpending operations within a desired time frame utilizing availableresources.

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the distributed storageand task (DST) client module 34 of FIG. 1, the network 24 of FIG. 1, anda set of DST execution units 1−n implemented at sites 1-3.Alternatively, the set of DST execution units may be implemented up toas many as n sites. Each DST execution unit may be implemented utilizingthe DST execution unit 36 of FIG. 1. The DST client module 34 includesthe outbound DST processing 80 of FIG. 3, the memory 88 of FIG. 3, andthe inbound DST processing 82 of FIG. 3. The DSN functions to accessdata 370 stored in the set of DST execution units. The accessingincludes storing the data 370 and retrieving the stored data to producerecovered data 378.

In an example of operation of the storing of the data 370, the outboundDST processing 80 dispersed storage error encodes the data 370 thatincludes a data segment to produce slices 372 that includes a set ofencoded data slices 1−n. Having produced the set of encoded data slices,the outbound DST processing 80 selects a subset of encoded data slicesof the set of encoded data slices for local redundancy generation. Theselecting may be based on one or more of an encoded data sliceaffiliation, historical slice retrieval reliability level information(e.g., by site, by the DST execution unit), interpreting an errormessage, and a predetermination. For example, the outbound DSTprocessing 80 selects encoded data slices 2, 3, and 4 of the set ofencoded data slices when encoded data slices 2, 3, and 4 are affiliatedwith storage by DST execution units 2, 3, and 4 at site 2 and sliceretrieval reliability information associated with site 2 indicates alevel of retrieval reliability that is less than a low retrievalreliability threshold level.

Having selected the subset of encoded data slices, the outbound DSTprocessing 80 dispersed storage error encodes the subset of encoded dataslices to produce one or more local redundant slices 374. For example,the outbound DST processing 80 dispersed storage error encodes encodeddata slices 2, 3, and 4 to produce local redundancy slices 2-4, 1 and2-4, 2. Having produced the one or more local redundancy slices threeand 74, the outbound DST processing 80 stores the one or more localredundancy slices in a local memory. For example, the outbound DSTprocessing 80 stores the local redundancy slices 2-4, 1 and 2-4, 2 inthe memory 88.

Having stored the one or more local redundancy slices 374, the outboundDST processing 80 facilitates storage of the set of encoded data slices1−n in the set of DST execution units 1−n. For example, the outbound DSTprocessing 80 issues, via the network 24, a set of write slice requeststo the set of DST execution units, where the set of write slice requestsincludes the set of encoded data slices 372. For instance, the outboundDST processing 80 sends encoded data slice 1 to DST execution unit 1,sends encoded data slices 2-4 to DST execution units 2-4 at site 2, andsends encoded data slices 5-n to DST execution units 5-n at site 3.

In an example of operation of the retrieving of the data 370, theinbound DST processing 82 issues read slice requests to the set ofstorage units, where the set of read slice requests includes a set ofslice names associated with the set of encoded data slices. The set ofDST execution units sends, via the network 24, available error-freeencoded data slices to the inbound DST processing unit 82 to producereceived slices 376. For example, DST execution unit 1 sends encodeddata slice 1, DST execution units 2 and 4 send encoded data slices 2 and4 when encoded data slice 3 is associated with a storage error, and DSTexecution units 5-n send encoded data slices 5-n.

Having received the encoded data slices 376, the inbound DST processing82 identifies a missing encoded data slice, where the missing encodeddata slices associated with the subset of encoded data slices. Forexample, the inbound DST processing 82 identifies that encoded dataslice 3 is missing.

Having identified the missing encoded data slice, the inbound DSTprocessing 82 generates a rebuilt encoded data slice for the missingencoded data slice utilizing at least one local redundancy slice 374.For example, the inbound DST processing 82 retrieves local redundancyslice 2-4, 1 from the memory 88, and dispersed storage error decodesreceived encoded data slices 2, 4 and local redundancy slice 2-4, 1 toproduce the rebuilt encoded data slice 3. Having produced the rebuiltencoded data slice, the inbound DST processing 82 dispersed storageerror decodes remaining received encoded data slices and the rebuiltencoded data slice to produce the recovered data 378.

FIG. 41B is a flowchart illustrating an example of reproducing datautilizing local redundancy in accordance the present invention. Themethod begins or continues at a storing step 380 where a processingmodule (e.g., of a distributed storage and task (DST) client module)dispersed storage error encodes a data segment to produce a set ofencoded data slices. The method continues at step 382 where theprocessing module selects a subset of encoded data slices of the set ofencoded data slices for local redundancy generation. The selecting maybe based on one or more of a site mapping, an error message, apredetermination, and a slice affiliation indicator.

The method continues at step 384 where the processing module dispersedstorage error encodes the subset of encoded data slices to produce oneor more local redundancy slices. The method continues at step 386 wherethe processing module temporarily stores the one or more localredundancy slices. The storing may include one or more of storing theone or more local redundancy slices in a local memory and establishing atime frame of storage indicating when to delete the one or more localredundancy slices. For example, the establishing includes indicating todelete when storage is confirmed of each encoded data slice of the setof encoded data slices. As another example, the establishing includesdeleting when a retrieval reliability indicator is greater than aretrieval reliability threshold level. As yet another example, theestablishing includes deleting when retrieving a dilution request. Themethod continues at step 388 where the processing module facilitatesstorage of the set of encoded data slices in a set of storage units.

The method begins or continues at a retrieving step 390 where theprocessing module issues a read threshold number of read slice requeststo the set of storage units. The method continues at step 392 where theprocessing module receives encoded data slices of the set of encodeddata slices. The method continues at step 394 where the processingmodule identifies a missing encoded data slice, where the missingencoded data slice is associated with the subset of encoded data slices.For example, the processing module identifies the missing slice whenreceiving less than a read threshold number of encoded data slices.

The method continues at step 396 where the processing module generates arebuilt encoded data slice for the missing encoded data slices utilizingat least one local redundancy slice and at least some of the receivedencoded data slices. For example, the processing module dispersedstorage error decodes remaining encoded data slices of the set ofencoded data slices and the at least one local redundancy slices toreproduce the subset of encoded data slices. The method continues atstep 398 where the processing module dispersed storage error decodes thereceived encoded data slices and the rebuilt encoded data slice toreproduce the recovered data segment.

FIGS. 42A-C are a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a plurality of distributedstorage and task (DST) client modules 1-4, etc., the network 24 of FIG.1, and a plurality of storage sets A-B. Alternatively, the DSN mayinclude any number of storage sets. Each storage set may include anumber of DST execution (EX) units in accordance with an informationdispersal algorithm (IDA) width. For example, the storage set A includesDST execution units 1-15 when utilized with an IDA width of 15 and thestorage set B includes DST execution units 1-6 when utilized with an IDAwidth of 6. Each DST execution unit may be implemented utilizing the DSTexecution unit 36 of FIG. 1. Hereafter, each DST execution unit may beinterchangeably referred to as a storage unit. Each DST client moduleincludes the outbound DST processing 80 of FIG. 3 and the inbound DSTprocessing 82 of FIG. 3. Hereafter, each of the DST client modules maybe interchangeably referred to as retrieving devices. For example, theDST processing unit 16 of FIG. 1 includes the DST client module 34 andmay retrieve the stored data object 400 as a retrieving device. The DSNfunctions to maintain data storage in accordance with an access metric.The maintaining includes one or more of storing a data object 400 in atleast one of the storage sets, re-storing the data object 400 in the atleast one of the storage sets, and facilitating retrieval of the dataobject 400.

FIG. 42A illustrates an example of operation of the storing of the dataobject 400 where the outbound DST processing 80 determines storageefficiency dispersal parameters 402 to utilize when initially storingthe data object 400 in at least one of the storage sets using a storageefficiency approach. Hereafter, the storage efficiency dispersalparameters 402 may be interchangeably referred to as first dispersedstorage error encoding parameters. The determining may be based on oneor more of an expected retrieval frequency, a storage utilization level,an available storage level, a storage efficiency goal, and apredetermination. The storage efficiency dispersal parameters 402includes an information dispersal algorithm (IDA) width=n, a decodethreshold number=k and a ratio of the decode threshold number to the IDAwidth such that the ratio is greater than a high threshold level toproduce storage efficiency greater than a storage efficiency thresholdlevel. For example, the outbound DST processing 80 determines thestorage efficiency dispersal parameters 402 to include a decodethreshold of 10 and an IDA pillar width of 15 such that the ratio is0.75 when the expected retrieval frequency is less than a high retrievalfrequency threshold level and as such, storage efficiency is moredesirable than throughput efficiency when subsequently accessing thedata object 400.

Having determined the storage efficiency dispersal parameters, theoutbound DST processing 80 facilitates storage of the data object 400 inthe storage set A when the storage set A is associated with the storageefficiency dispersal parameters 402 (e.g., includes 15 storage unitswhen the IDA width is 15). For example, the outbound DST processing 80dispersed storage error encodes the data object 400 using the storageefficiency dispersal parameters 402 to produce a first plurality of setsof encoded data slices A1-A15 and sends, via the network 24, the firstplurality of sets of encoded data slices to the DST execution units 1-15of the storage set A for storage.

FIG. 42B illustrates an example of operation of the re-storing of thedata object where the DST client module 1 determines that an accessmetric regarding the encoded data object 400 exceeds an accessthreshold, where the encoded data object 400 is stored as the firstplurality of sets of encoded data slices based on the first dispersedstorage error encoding parameters. The access metrics includes one ormore of network traffic loading information (e.g., a utilization levelof the network 24), and access rate of the data object 400 (e.g., by theplurality of DST client modules), and storage unit loading of the set ofstorage units (e.g., storage set A) storing the first plurality of setsof encoded data slices (e.g., one or more storage units of the storageset A are overloaded). The determining may be based on one or more ofinterpreting a determination schedule (e.g., assess the access metricevery 10 minutes), receiving an access metric verification request(e.g., from a managing unit), and receiving a retrieval request 404 withregards to recovering the data object 400.

When the access metric exceeds the access threshold, the inbound DSTprocessing 82 retrieves, via the network 24, a first decode thresholdnumber of encoded data slices (e.g., encoded data slices A1-A10) of eachset of the first plurality of sets of encoded data slices. Havingretrieved the encoded data slices, the inbound DST processing 82 decodesthe first decode threshold number of encoded data slices (e.g., encodeddata slices A1-A10) of each set to recover the data object as recovereddata 408. Hereafter, the recovered data 408 may be interchangeablyreferred to as recovered data object 408.

Having produce the recovered data 408, the outbound DST processing 80re-encodes the recovered data object 408 using second dispersed storageerror encoding parameters to produce a re-encoded data object, where there-encoded data object includes a second plurality of sets of encodeddata slices and where a second decode threshold number associated withthe second dispersed storage error encoding parameters is less than thefirst decode threshold number. Hereafter, the second dispersed storageerror encoding parameters may be interchangeably referred to asthroughput efficiency dispersal parameters 406.

At least one of the inbound DST processing 82 and the outbound DSTprocessing 80 may determine the throughput efficiency dispersalparameters 406 based on one or more of the access rate of the dataobject, a number of the retrieving devices, the network traffic loadinginformation, a predetermination, a historical access information, and adesired number of simultaneous data accesses. As a specific example, theinbound DST processing 82 determines the second decode threshold numberto be less than or equal to one-half of the first decode thresholdnumber when a desired level of network transactions is at least half ofthat associated with the first dispersed storage error encodingparameters. As another specific example, the inbound DST processing 82determines the second decode threshold number to be less than or equalto one-half of a total number of encoded data slices in a set of thesecond plurality of sets of encoded data slices when a number of desiredsimultaneous data accesses is at least two. For instance, the inboundDST processing 82 determines the second decode threshold number to betwo when the IDA width of the second dispersed storage error encodingparameters is six when the number of desired simultaneous data accessesis at least three.

Having re-encoded the recovered data object 408 using the seconddispersed storage error encoding parameters, the outbound DST processing80 sends, via the network 24, the second plurality of sets of encodeddata slices to storage units of the DSN for storage. For example, theoutbound DST processing 80 sends, via the network 24, encoded dataslices B1-B6 to the DST execution units 1-6 of the storage set B forstorage. Having facilitated storage of the second plurality of sets ofencoded data slices, the outbound DST processing 80 may send a messageto retrieving devices of the DSN, where the message indicates use of thesecond plurality of sets of encoded data slices for the data object. Forexample, the outbound DST processing 80 updates system registryinformation to indicate one or more of the use of the second pluralityof sets of encoded data slices for the data object and the seconddispersed storage error encoding parameters. FIG. 42C illustrates anexample of operation of the facilitating of the retrieving of the dataobject where one or more of the DST client modules (e.g., retrievingdevices) receives, substantially simultaneously, the retrieval request404 for the re-encoded data object. Having received the retrievalrequests 404, each of the DST client modules identifies particularencoded data slices of each of the sets of encoded data slices of thesecond plurality of sets of encoded data slices for retrieval andissues, via the network 24, read slice requests to the correspondingstorage units of the storage set B. The identifying may be based on oneor more of a predetermination, the system registry information, a roundrobin selection process, and a random selection of all possiblepermutations of the second decode threshold number of encoded dataslices of each set of the second plurality of sets of encoded dataslices. For example, DST client module 1 selects and retrieves encodeddata slices B1-B2, DST client module 2 selects and retrieves encodeddata slices B3-B4, DST client module 3 selects and retrieves encodeddata slices B5-B6, and DST client module 4 selects and retrieves encodeddata slices B1-B2 (e.g., wraparound in the round robin selectionprocess).

Having issued the read slice requests, each storage unit in a firstsubset (e.g., storage units 1 and 2) of the storage units, outputs, viathe network 24, an encoded data slice (e.g., encoded data slices B1and/or B2) of a set of the second plurality of sets of encoded dataslices in response to a first retrieval request for the re-encoded dataobject. Each storage unit in a second subset (e.g., storage units 3-4)of the storage units, outputs, via the network 24, an encoded data slice(e.g., encoded data slices B3 and/or B4) of the set of the secondplurality of sets of encoded data slices in response to a secondretrieval request for the re-encoded data object. The storage units mayreceive the first and second retrieval requests for the re-encoded dataobject from first and second retrieving devices of the retrievingdevices at substantially the same time (e.g., before completion of onerequest, the other was received). Each DST client modules receives theencoded data slices and reproduces the recovered data 408. For example,DST client module 2 receives encoded data slices B3-B4 to reproduce therecovered data 408 and DST client module 3 receives encoded data slicesB5-B6 to reproduce the recovered data 408 etc.

Alternatively, or in addition to, when the access metric drops below theaccess threshold (e.g., with some hysteresis), the DST client module 1sends a second message to the retrieving devices, where the secondmessage indicates use of the first plurality of sets of encoded dataslices for the data object (e.g., from storage set A). Furtheralternatively, the DST client module 1 sends, via the network 24,deletion messages to the storage units of the storage set B, where thedeletion messages instruct the storage units to delete the secondplurality of sets of encoded data slices.

FIG. 42D is a flowchart illustrating an example of maintaining datastorage in accordance with an access metric in accordance the presentinvention. In particular, a method is presented for use in conjunctionwith one or more functions and features described in conjunction withFIGS. 1-39, 42A-C, and also FIG. 42D. The method begins at step 410where a processing module of a computing device (e.g., of a distributedstorage and task (DST) processing unit) of one or more computing devicesof a dispersed storage network (DSN) determines that an access metricregarding an encoded data object exceeds an access threshold, where theencoded data object is stored as a first plurality of sets of encodeddata slices based on first dispersed storage error encoding parameters.

When the access metric exceeds the access threshold, the methodcontinues at step 412 where the processing module retrieves a firstdecode threshold number of encoded data slices of each set of the firstplurality of sets of encoded data slices. The method continues at step412 where the processing module decodes the first decode thresholdnumber of encoded data slices of each set to recover the data object.

The method continues at step 414 where the processing module re-encodesthe recovered data object using second dispersed storage error encodingparameters to produce a re-encoded data object, where the re-encodeddata object includes a second plurality of sets of encoded data slicesand where a second decode threshold number associated with the seconddispersed storage error encoding parameters is less than the firstdecode threshold number. For example, the second decode threshold numberis less than or equal to one-half of the first decode threshold number.As another example, the second decode threshold number is less than orequal to one-half of a total number of encoded data slices in a set ofthe second plurality of sets of encoded data slices.

The method continues at step 416 where the processing module outputs thesecond plurality of sets of encoded data slices to storage units of theDSN for storage therein. The method continues at step 418 where theprocessing module sends a message to retrieving devices of the DSN,where the message indicates use of the second plurality of sets ofencoded data slices for the data object. For example, the processingmodule updates system registry information to indicate the usage of thesecond plurality of sets of encoded data slices for the data object.

The method continues at step 420 where each storage unit in a firstsubset of the storage units outputs an encoded data slice of a set ofthe second plurality of sets of encoded data slices in response to afirst retrieval request for the re-encoded data object. The methodcontinues at step 422 where each storage unit in a second subset of thestorage units outputs an encoded data slice of the set of the secondplurality of sets of encoded data slices in response to a secondretrieval request for the re-encoded data object. The storage units mayreceive the first and second retrieval requests for the re-encoded dataobject from first and second retrieving devices of the retrievingdevices at substantially the same time (e.g., before completion of onerequest, the other was received).

When the access metric drops below the access threshold (e.g., with somehysteresis) the method continues at step 424 where the processing modulesends a second message to the retrieving devices, where the secondmessage indicates use of the first plurality of sets of encoded dataslices for the data object. The method continues at step 426 where theprocessing module sends deletion messages to the storage units, wherethe deletion messages instruct the storage units to delete the secondplurality of sets of encoded data slices.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section(e.g., a non-transitory computer readable storage medium) that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of the dispersed storagenetwork (DSN), cause the one or more computing devices to perform any orall of the method steps described above.

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the distributed storageand task (DST) client module 34 of FIG. 1, the network 24 of FIG. 1, anda plurality of storage sets 1-2. Alternatively, the DSN may include anynumber of storage sets. Each storage set includes a set of any number ofn DST execution (EX) units 1−n. Each DST execution unit may beimplemented utilizing the DST execution unit 36 of FIG. 1. The DSTclient module 34 includes the outbound DST processing 80 of FIG. 3, theinbound DST processing 82 of FIG. 3, and a transfer module 430. Thetransfer module 430 may be implemented utilizing the processing module84 of FIG. 3. Alternatively, the transfer module 430 may be implementedby any DST execution unit of the DSN. The DSN functions to access dataand to balance storage of the data stored in the plurality of storagesets. The accessing includes storing the data and retrieving storeddata.

In an example of operation of the storing of the data, the outbound DSTprocessing 80 receives a first data object 432, dispersed storage errorencodes the first data object 432 to produce a first plurality of setsof encoded data slices 1−n, sends, via the network 24, the firstplurality of sets of encoded data slices 1−n 434 to the DST executionunits 1−n of the storage set 1 for storage. As another example, theoutbound DST processing 80 receives a second data object, dispersedstorage error encodes the second data object to produce a secondplurality of sets of encoded data slices 1−n, sends, via the network 24,the second plurality of sets of encoded data slices 1−n to the DSTexecution units 1−n of the storage set 2 for storage.

In an example of operation of the retrieving of the data, the inboundDST processing 82 generates a plurality of sets of slice namesassociated with the plurality of sets of encoded data slices associatedwith the first data object, generates a read threshold number of readslice requests that includes a read threshold number of slice names ofeach set of slice names, sends, via the network 24, the read thresholdnumber of read slice requests to a read threshold number of DSTexecution units of the storage set 1, receives encoded data slices 438,and dispersed storage error decodes a decode threshold number of encodeddata slices of each set of encoded data slices of the first plurality ofsets of encoded data slices to reproduce the first data object asrecovered data 440

In an example of operation of the balancing of the storage of the data,the transfer module 430 detects that an input/output loading level of astorage set of the plurality of storage sets is greater than a highloading threshold level. The detecting includes at least one ofinterpreting a system activity logging record, interpreting a loadingmeasurement, receiving an error message, and counting data accessrequests. Such input/output loading may result from one or more ofstoring new encoded data slices and retrieving previously stored encodeddata slices.

When detecting the loading level of the storage set is greater than thehigh loading threshold level, the transfer module 430 identifies ahigh-demand data object stored in the storage set. For example, thetransfer module 430 counts data access requests for one or more dataobjects to identify the high-demand data object associated with thegreatest number of access requests. Having identified the high-demanddata object stored in the storage set, the transfer module 430identifies another storage set, where the other storage set isassociated with an input/output loading level that is less than the highloading threshold level.

Having identified the other storage set, the transfer module 430identifies a low-demand data objects stored in the other storage setthat is associated with a data size that is within a size thresholdlevel of a data size of the high-demand data object. For example, thetransfer module obtains slice transfer information 436 from the otherstorage set and the storage set to identify data sizes of stored dataobjects. Alternatively, the transfer module 430 issues slice transferinformation 436 to the other storage set, where the slice transferinformation 436 includes a request to swap the identified low-demanddata object for the high-demand data object.

Having identified the low-demand data object stored in the other storageset, the transfer module 430 facilitates swapping storage of thehigh-demand data object in the low-demand data object between thestorage set and the other storage set. For example, the transfer modulerecovers the high-demand data object from the storage set, stores thehigh-demand data object in the other storage set, recovers the low dataobject from the other storage set, and stores the low data object in thestorage set. As another example, the transfer module 430 issues transferslice requests to the storage set and the other storage set to requesttransfer of encoded data slices of the high-demand data object and thelow-demand data object. Having facilitated swapping of the storage, thetransfer module 430 updates an association of the high-demand dataobject and the low-demand data object in storage locations. The updatingincludes at least one of updating a directory and updating a dispersedhierarchical index associated with the stored data.

FIG. 43B is a flowchart illustrating an example of balancing loading ofstorage resources in accordance the present invention. The method beginsor continues at step 442 where a processing module (e.g., of a transfermodule) detects that a loading level of a storage set is greater than ahigh loading threshold level. The method continues at step 444 where theprocessing module identifies a high-demand data object stored in thestorage set. The method continues at step 446 where the processingmodule determines a size of the high-demand data object. For example,the processing module accesses a storage record within a storage unit ofthe storage set.

The method continues at step 448 where the processing module identifiesanother storage set that is associated with a loading level that is lessthan the high loading threshold level. The method continues at step 450where the processing module identifies a low-demand data object storedin the other storage said that is associated with a size that is withina size threshold level of a size of the high-demand data object.

The method continues at step 452 where the processing module facilitatesswapping storage of the high-demand data object in the low-demand dataobject between the storage set and the other storage set. For example,the processing module directly moves data objects by retrieving andstoring encoded data slices. As another example, the processing moduleissues transfer encoded data slice commands. The method continues atstep 454 where the processing module updates a record that associatesdata objects in storage set identifiers. For example, the processingmodule associates the high-demand data object with the other storageset, disassociates the high-demand data object from the storage set,associates the low-demand data object with the storage set, anddisassociates the low-demand data object with the other storage set.

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a rebuilding module 460,the network 24 of FIG. 1, and a set of distributed storage and task(DST) execution (EX) units implemented at sites 1-3. Alternatively, theDST execution units may be implemented at any number of sites. Each DSTexecution unit may be implemented utilizing the DST execution unit 36 ofFIG. 1. The rebuilding module 460 includes the DST client module 34 ofFIG. 1 and the memory 88 of FIG. 3. The rebuilding module 460 may beimplemented utilizing at least one of the DST processing unit 16 of FIG.1, any one or more DST execution units of the DSN, and the DST integrityprocessing unit 20 of FIG. 1. The DSN functions to rebuild an encodeddata slice to produce a rebuilt encoded data slice when a storage erroris detected for data stored as a plurality of sets of encoded dataslices 1−n in the set of DST execution units 1−n.

In an example of operation of the rebuilding of the encoded data slice,the DST client module 34 of the rebuilding module identifies the encodeddata slice associated with a detected storage error, where a datasegment is dispersed storage error encoded to produce a set of encodeddata slices that includes the encoded data slices and where the set ofencoded data slices is stored in the set of DST execution units andwhere the set of DST execution units is associated with a plurality ofassociate a network topology configurations (e.g., number of DSTexecution units per site). The identifying includes at least one ofdetecting a missing encoded data slice, detecting a corrupted slice,receiving an indication of error, and interpreting an error message.

Having identified the encoded data slice associated with the detectedstorage error, the DST client module 34 determines a time frame forreplacement of the encoded data slice with the rebuild encoded dataslice. For example, the DST client module 34 determines how longpostponement of rebuilding can be to achieve a desired level ofretrieval reliability. The determining may be based on one or more ofhistorical rebuilding records, historical data retrieval reliabilityrecords, a goal for retrieval reliability, and availability status ofthe DST execution units.

Having determined the time frame for replacement of the encoded dataslice, the DST client module 34 determines a plurality of expectedloading levels versus time over the time frame for the plurality ofassociated network topology configurations. For example, the DST clientmodule 34 obtains expected loading information for each DST executionunit.

For each of the plurality of associated network topology configurations,the DST client module 34 identifies a sub-time frame of the time frameassociated with an expected loading level that is less than a highloading threshold level. For example, the DST client module 34identifies the sub-time frames from received expected loadinginformation from each of the DST execution units.

Having identified the sub-time frame, the DST client module 34 generatesa rebuilding schedule where the rebuilding schedule identifies when,over the time frame, to access each of the plurality of associatednetwork topology configurations to gather slice rebuilding information464 based on the identified sub-time frame of the associated networktopology. For example, the DST client module 34 identifies that a subtime frame at t1 shall be utilized to acquire slice rebuildinginformation 1 from DST execution unit 1 at site 1, identifies that a subtime frame at t2 shall be utilized to acquire slice rebuildinginformation 2 from DST execution units 2-4 at site 2, and identifiesthat a sub time frame at t3 shall be utilized to acquire slicerebuilding information 3 from DST execution units 5-n at site 3 suchthat an extra burden of processing slice rebuilding information requests462 can be accommodated in light of other loading of the set of DSTexecution units.

Having generated the rebuilding schedule, for each of the plurality ofassociated network topology configurations, the DST client module 34obtains the slice rebuilding information 464 in accordance with therebuilding schedule. For example, the DST client module 34 issues, viathe network 24, a slice rebuilding information request 1 at time t1 toDST execution unit 1 at site 1, receives slice rebuilding information 1as slice rebuilding information, and stores the slice rebuildinginformation 1 in the memory 88; issues, via the network 24, a slicerebuilding information request 2 at time t2 to DST execution unit 2 atsite 2, receives slice rebuilding information 2 as further slicerebuilding information, and stores the slice rebuilding information 2 inthe memory 88; issues, via the network 24, a slice rebuildinginformation request 3 at time t3 to DST execution unit 5 at site 3,receives slice rebuilding information 3 as still further slicerebuilding information, and stores the slice rebuilding information 3 inthe memory 88.

The slice rebuilding information 464 includes at least one of aretrieved encoded data slice and a partially encoded data slice for theencoded data slice associated with the storage error based on one ormore locally stored encoded data slices. For example, the slicerebuilding information 2 includes encoded data slice 2 and 4 whenencoded data slice 3 is not available. As another example, the slicerebuilding information 2 includes a partially encoded data slice for theencoded data slice of the storage error based on the encoded data slices2 and 4. For instance, DST execution unit 2 generates a first partiallyencoded data slice for the encoded data slice 3 associated with thestorage error based on the encoded data slice 2, DST execution unit 4generates a second partially encoded data slice for the encoded dataslice 3 based on the encoded data slice 4, and DST execution unit 2performs an exclusive OR function on the first and second partialencoded data slices to produce the slice rebuilding information 2.

Generating of a partially encoded data slice includes obtaining anencoding matrix utilized to generate the encoded data slice to berebuilt, reducing the encoding matrix to produce a square matrix thatexclusively includes rows associated with a decode threshold number ofstorage units, inverting the square matrix to produce an invertedmatrix, matrix multiplying the inverted matrix by a locally storedencoded data slice associated with the storage unit to produce a vector,and matrix multiplying the vector by a row of the encoding matrixcorresponding to the encoded data slice to be rebuilt to produce thepartial encoded data slice.

When receiving a sufficient amount of slice rebuilding information 464,the DST client module 34 of the rebuilding module 460 generates therebuilt encoded data slice using the slice rebuilding information 464(e.g., retrieved from the memory 88). For example, when receivingencoded data slices as the slice rebuilding information, the DST clientmodule 34 dispersed storage error decodes a decode threshold number ofreceived encoded data slices to produce a recovered data segment anddispersed storage error encodes the recovered data segment to producethe rebuilt encoded data slice. As another example, when receivingpartially encoded data slices as the sliced rebuilding information, theDST client module 34 performs the exclusive OR function on the partiallyencoded data slices to produce the rebuilt encoded data slice.

Having produced the rebuilt encoded data slice, the DST client module 34facilitates storage of the rebuilt encoded data slice. For example, theDST client module 34 issues, via the network 24, a write slice requestto DST execution unit 3, where the write slice request includes therebuilt encoded data slice.

FIG. 44B is a flowchart illustrating an example of rebuilding an encodeddata slice in accordance the present invention. The method begins orcontinues at step 466 where a processing module (e.g., of a distributedstorage and task (DST) client module) identifies an encoded data sliceassociated with a detected storage error, where the encoded data slicesstored in a storage unit of a group of storage units where a set ofstorage units includes a plurality of groups of storage units. Themethod continues at step 468 where the processing module determines atime frame for replacement of the encoded data slice with a rebuiltencoded data slice. For example, the processing module utilizes apredetermined maximum time frame value from a system registry.

For each group of storage units, the method continues at step 470 wherethe processing module determines an expected loading level over the timeframe. For example, the processing module identifies a current loadinglevel. As another example, the processing module interprets a historicalloading level record. For each group of storage units, the methodcontinues at step 472 where the processing module identifies asub-timeframe of the timeframe where the sub-timeframe is associatedwith an expected loading level that is less than a high loadingthreshold level. For example, the processing module identifies a lightlyloaded sub-timeframe. The method continues at step 474 where theprocessing module generates a rebuilding schedule based on theidentified sub-time frames. For example, the processing module schedulesretrieval of encoded data slice rebuilding information when lightlyloaded for each group of storage units.

For each group of storage units, the method continues at step 476 wherethe processing module obtains slice rebuilding information in accordancewith the rebuilding schedule. For example, the processing module issuesa slice rebuilding information request at a time frame of the rebuildingschedule and receives the slice rebuilding information.

When receiving a sufficient amount of slice rebuilding information(e.g., a decode threshold number of encoded data slices, one or morepartial encoded data slices that represents at least a decode thresholdnumber of partial encoded data slices), the method continues at step 478where the processing module generates the rebuilt encoded data slicesusing the received slice rebuilding information. For example, theprocessing module decodes the received slice rebuilding information toproduce the rebuilt encoded data slice. The method continues at step 480where the processing module facilitates storage of the rebuilt encodeddata slice.

FIGS. 45A-C are a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the distributed storageand task (DST) client module 34 of FIG. 1, the network 24 of FIG. 1, anda storage set 490. The storage set 490 includes a set of DST execution(EX) units. The storage set 490 may include a number of DST executionunits in accordance with a width of dispersed storage error encodingparameters, where the dispersed storage error encoding parametersincludes the width number and a decode threshold number. For instance,the storage set 490 includes DST execution units 1-9. Alternatively, thestorage set 490 may include any number of DST execution units. Each DSTexecution unit may be implemented utilizing the DST execution unit 36 ofFIG. 1. Hereafter, each DST execution unit may be referred tointerchangeably as a storage unit and the storage set 490 may beinterchangeably referred to as a set of storage units. The DST clientmodule 34 includes the inbound DST processing 82 of FIG. 3 and one ormore outbound DST processings 1-2. Each outbound DST processing may beimplemented utilizing the outbound DST processing 80 of FIG. 3.Alternatively two or more DST client modules 34 may be utilized toimplement the one or more outbound DST processings. The DSN functions tostore data in the storage set and to verify a status level (e.g.,revision level) of stored encoded data slices to facilitate furtherstorage and subsequent recovery of revision compliant (e.g., a desiredrevision level) stored data from the storage set 490.

FIG. 45A illustrates steps of an example of operation of the verifyingof the status level of the stored encoded data slices where eachoutbound DST processing 1-2 dispersed storage error encodes a commondata object of different revisions (e.g., data object A revision 1, adata object A revision 2) using the dispersed storage error encodingparameters to produce one or more of sets of encoded data slices 1-9.For example, the outbound DST processing 1 divides the data object Arevision 1 into a plurality of data segments and encodes a data segmentof the plurality of data segments of the data object A revision 1 inaccordance with the dispersed storage error encoding parameters toproduce a set of encoded data slices that includes encoded data slice 1revision 1 through encoded data slice 9 revision 1. The dispersedstorage error encoding parameters includes the decode threshold numberand the width number, where the decode threshold number corresponds to aminimum number of encoded data slices of the set of encoded data slicesthat are needed to recover the data segment. The width numbercorresponds to a total number of encoded data slices in the set ofencoded data slices and the decode threshold number is less than orequal to one-half of the width number (e.g., a replication-typeinformation dispersal algorithm (IDA) and/or dispersed storage errorcoding function). As such, it is possible to simultaneously recover datafrom two or more groups of a decode threshold number of encoded dataslices of each set of encoded data slices where each group of a decodethreshold number of encoded data slices may be associated with a commonor a different revision level.

Having produced the set of encoded data slices, the outbound DSTprocessing 1 sends, via the network 24, the set of encoded data slicesto the storage set 490 for storage (e.g., where a corresponding set ofslice names are also sent with the set of encoded data slices). In asimilar fashion, the outbound DST processing 2 dispersed storage errorencodes a data segment of the data object A revision 2 to produceanother set of encoded data slices that includes encoded data slice 1revision 2 through encoded data slice 9 revision 2. Having produced theother set of encoded data slices, the outbound DST processing 2 maysend, substantially simultaneously with the sending of the set ofencoded data slices by the outbound DST processing 1, via the network24, the other set of encoded data slices to the storage set 490 forstorage (e.g., where the same corresponding set of slice names are alsosent with the other set of encoded data slices).

From time to time, it is possible, due to varying factors including oneor more of conditions of the network 24, loading levels of DST executionunits, storage or processing errors by the DST execution units, andother causes, for the different revisions of the sets of encoded dataslices utilizing a common set of slice names to be stored in differentstorage units of the storage set 490. For instance, the revision 2 levelof encoded data slices may have been successfully stored in the DSTexecution units 1, 2, 3, 7, 8, and 9 while the revision 1 level ofencoded data slices may have been successfully stored in the DSTexecution units 4, 5, and 6. As such, it is possible to recover a datasegment of two revisions of the data object A by retrieving and decodingtwo encoded data slices of DST execution units 1, 2, 3, 7, 8, and 9 orfrom another two encoded data slices of DST execution units 4, 5, and 6when the decode threshold number is 2.

FIG. 45B illustrates further steps of the example of operation of theverifying of the status level of the stored encoded data slices wherethe inbound DST processing 82 retrieves a decode threshold number ofencoded data slices of the set of encoded data slices from a firstgrouping of storage units of the DSN. For example, the inbound DSTprocessing 82 issues, via the network 24, read slice requests forencoded data slices 1 and 2 to the DST execution units 1-2 and receivesa first decode threshold number of encoded data slices (e.g., encodeddata slice 1 revision 2 and encoded data slice 2 revision 2).

Having received the decode threshold number of encoded data slices, theinbound DST processing 82 determines whether each encoded data slice ofthe first decode threshold number of the encoded data slices have a samestatus level (e.g., same revision level, i.e., revision level 2). Wheneach encoded data slice of the first decode threshold number of theencoded data slices have the same status level, the inbound DSTprocessing 82 uses the first decode threshold number of encoded dataslices as the decode threshold number of encoded data slices. Forexample, the inbound DST processing 82 uses the first decode thresholdnumber of encoded data slices as the decode threshold number of encodeddata slices when encoded data slices 1 and 2 both have the same revisionlevel 2.

When each encoded data slice of the first decode threshold number of theencoded data slices do not have the same status level, the inbound DSTprocessing 82 facilitates retrieving a second decode threshold number ofencoded data slices and receives the second decode threshold number ofencoded data slices (e.g., where at least one encoded data slice isdifferent than the first set). When each encoded data slice of thesecond decode threshold number of the encoded data slices have the samestatus level, the inbound DST processing 82 uses the second decodethreshold number of encoded data slices as the decode threshold numberof encoded data slices.

FIG. 45C illustrates further steps of the example of operation of theverifying of the status level of the stored encoded data slices where,to verify that the decode threshold number of encoded data slices is ofa common status level (e.g., a revision level, a version, a similar timestamp associated with a time of creation of encoded data slice, similaraccess permissions, etc.) as other encoded data slices of the set ofencoded data slices, the inbound DST processing 82 determines a firststatus level indication of the retrieved decode threshold number ofencoded data slices. For example, the inbound DST processing 82identifies revision 2 as the first status level indication of theretrieved decode threshold number of encoded data slices that includesencoded data slices 1 and 2.

Having determined the first status level indication, the inbound DSTprocessing 82 sends, via the network 24, check status request messagesto a second grouping of storage units of the DSN, where a check statusrequest message of the check status request messages is requesting thata storage unit of the second grouping of storage units provide a statuslevel indication of one of the other encoded data slices stored by thestorage unit. The inbound DST processing 82 may determine a number ofencoded data slices of the other encoded data slices that issubstantially equal to a read check number, where the read check numberis in a range of numbers between the decode threshold number and thewidth number minus the decode threshold number. The determining may bebased on one or more of achieving a satisfactory level of accuracy ofpredicting the indication of the common status level. For example, theinbound DST processing 82 determines the read check number to be 8 whenthe width is 9 when a highest level of accuracy is desired. As anotherexample, the inbound DST processing 82 determines the read check numberto be 6 when understanding the status level indication of 6 of 9 encodeddata slices is sufficient. For instance, the inbound DST processing 82establishes the number of check status request messages as 4 when theread check number is 6 and the decode threshold number is 2.

As an example of the sending of the check status request messages, theinbound DST processing 82 sends, via the network 24, four check requests3-6 (e.g., that includes slice names corresponding to encoded dataslices 3-6) to the corresponding DST execution units 3-6. Subsequent tosending the check status request messages, the inbound DST processing 82receives, via the network 24, check status response messages, where acheck status response message of the check status response messagesincludes the status level indication of the one of the other encodeddata slices. For example, the inbound DST processing 82 receives checkresponses 3-6, where the check responses 3-6 indicates that DSTexecution unit 3 is storing encoded data slice 3 revision 2, DSTexecution unit 4 is storing encoded data slice 4 revision 1, DSTexecution unit 5 is storing encoded data slice 5 revision 1, and DSTexecution unit 6 is storing encoded data slice 6 revision 1.

Having received the check status response messages, the inbound DSTprocessing 82 processes the check response messages to produce a secondstatus level indication. For example, the inbound DST processing 82processes the check responses (e.g., indicating one revision 2 and threerevision 1's) to produce the second status level indication thatincludes an indication of revision 1 when at least a decode thresholdnumber of encoded data slices associated with revision 1 are present. Asanother example, the inbound DST processing 82 processes the checkresponses to produce the second status level indication that includes anindication of revision 2 when revision 2 is a highest revision level ofthe received check responses (e.g., which does not conflict with thefirst status level indication).

When the second status level indication is substantially equal to thefirst status level indication, the inbound DST processing 82 indicatesthat the decode threshold number of encoded data slices is of the commonstatus level as the other encoded data slices. When the decode thresholdnumber of encoded data slices is of the common status level as the otherencoded data slices, the inbound DST processing 82 may decode the decodethreshold number of encoded data slices to recover the data segmentcontribute to producing recovered data 492.

When the second status level indication is not substantially equal tothe first status level indication, the inbound DST processing 82determines whether to maintain in the first and second groupings ofstorage units encoded data slices having different status levelindications (e.g., to keep different revisions, or versions) or toupdate the encoded data slices having different status level indications(e.g., update all to a most current revision level or version). Forexample, when the second status level indication is greater than thefirst status level indication, the inbound DST processing 82 sends, viathe network 24, a new retrieval request for the decode threshold numberof encoded data slices having the second status level indication to thesecond grouping of storage units of the DSN (e.g., second group includesat least one different storage unit than the first group). For instance,the inbound DST processing 82 retrieves encoded data slices 4 and 5associated with revision 1.

As another example of determining whether to maintain encoded dataslices having different status level indications, when the second statuslevel indication is less than the first status level indication, theinbound DST processing 82 determines whether to retrieve the decodethreshold number of the other encoded data slices (e.g., when desiringboth revisions). The determining may be based on one or more of dataconcurrency of the data object, time concurrency of write requests ofthe data segment (e.g., overlapping write requests where the first andsecond revs have different data), a request for all status levels of thedata segment, and user identifiers of the first and second status levelsof the data segment (e.g., an inter-dependency between users to insurethat they each see revisions made by the other). When the determinationis to retrieve the decode threshold number of the other encoded dataslices, the inbound DST processing 82 retrieves, via the network 24, thedecode threshold number of the other encoded data slices (e.g., encodeddata slices 4 and 5) and decodes the decode threshold number of theother encoded data slices to recover the data segment having the secondstatus level (e.g., revision 1).

Alternatively, the inbound DST processing 82 decodes the decodethreshold number of the encoded data slices to recover the data segmenthaving the first status level and when the decode threshold number ofthe other encoded data slices was retrieved based on the timeconcurrency of write requests of the data segment, the inbound DSTprocessing 82 merges changes of the data segment having the secondstatus level indication into the data segment having the first statuslevel indication. For example, merging the data segments to providemerged data revisions.

FIG. 45D is a flowchart illustrating an example of verifying a statuslevel of stored encoded data slices in a dispersed storage network inaccordance the present invention. In particular, a method is presentedfor use in conjunction with one or more functions and features describedin conjunction with FIGS. 1-39, 45A-C, and also FIG. 45D. The methodbegins or continues at step 500 where a processing module of a computingdevice (e.g., of the distributed storage and task (DST) processing unit16 of FIG. 1 that includes the DST client module 34 of FIG. 1) of one ormore computing devices of a dispersed storage network (DSN) retrieves adecode threshold number of encoded data slices of a set of encoded dataslices from a first grouping of storage units of the DSN, where a datasegment of a data object is encoded in accordance with dispersed storageerror encoding parameters to produce the set of encoded data slices. Thedispersed storage error encoding parameters includes the decodethreshold number and the width number, where the decode threshold numbercorresponds to a minimum number of encoded data slices of the set ofencoded data slices that are needed to recover the data segment and thewidth number corresponds to a total number of encoded data slices in theset of encoded data slices. The decode threshold number is less than orequal to one-half of the width number.

In an example of the retrieving of the decode threshold number ofencoded data slices, the processing module receives a first decodethreshold number of encoded data slices, determines whether each encodeddata slice of the first decode threshold number of the encoded dataslices have a same status level. When each encoded data slice of thefirst decode threshold number of the encoded data slices have the samestatus level, the processing module uses the first decode thresholdnumber of encoded data slices as the decode threshold number of encodeddata slices. When each encoded data slice of the first decode thresholdnumber of the encoded data slices do not have the same status level, theprocessing module receives a second decode threshold number of encodeddata slices (e.g., at least one slice different than the first set).When each encoded data slice of the second decode threshold number ofthe encoded data slices have the same status level, the processingmodule uses the second decode threshold number of encoded data slices asthe decode threshold number of encoded data slices.

To verify that the decode threshold number of encoded data slices is ofa common status level as other encoded data slices of the set of encodeddata slices, the method continues at step 502 where the processingmodule determines a first status level indication of the retrieveddecode threshold number of encoded data slices. The method continues atstep 504 where the processing module sends check status request messagesto a second grouping of storage units of the DSN, where a check statusrequest message of the check status request messages is requesting thata storage unit of the second grouping of storage units provide a statuslevel indication of one of the other encoded data slices stored by thestorage unit. A number of encoded data slices of the other encoded dataslices is substantially equal to a read check number, where the readcheck number is in a range of numbers between the decode thresholdnumber and the width number minus the decode threshold number.

The method continues at step 506 where the processing module receivescheck status response messages, where a check status response message ofthe check status response messages includes the status level indicationof the one of the other encoded data slices. The method continues atstep 508 where the processing module processes the check responsemessages to produce a second status level indication. When the secondstatus level indication is not substantially equal to the first statuslevel indication, the method branches to step 514. When the secondstatus level indication is substantially equal to the first status levelindication, the method continues to step 510.

When the second status level indication is substantially equal to thefirst status level indication, the method continues at step 510 wherethe processing module indicates that the decode threshold number ofencoded data slices is of the common status level as the other encodeddata slices. When the decode threshold number of encoded data slices isof the common status level as the other encoded data slices, the methodcontinues at step 512 where the processing module decodes the decodethreshold number of encoded data slices to recover the data segment.

When the second status level indication is not substantially equal tothe first status level indication, the method continues at step 514where the processing module determines whether to maintain in the firstand second groupings of storage units encoded data slices havingdifferent status level indications (e.g., keep the different revisions,or versions) or to update the encoded data slices having differentstatus level indications (e.g., update all to a most current rev levelor version). When the second status level indication is less than thefirst status level indication, the method branches to step 518. When thesecond status level indication is greater than the first status levelindication, the method continues to step 516.

When the second status level indication is greater than the first statuslevel indication, the method continues at step 516 where the processingmodule sends a new retrieval request for the decode threshold number ofencoded data slices having the second status level indication to thesecond grouping of storage units of the DSN. For example, the secondgroup includes at least one different storage unit than the first group.

When the second status level indication is less than the first statuslevel indication, the method continues at step 518 where the processingmodule determines whether to retrieve the decode threshold number of theother encoded data slices (e.g., when desiring both revisions). Thedetermining may be based on one or more of data concurrency of the dataobject, time concurrency of write requests of the data segment (e.g.,overlapping write requests where the first and second revs havedifferent data), a request for all status levels of the data segment,and user identifiers of the first and second status levels of the datasegment (e.g., an inter-dependency between users to insure that theyeach see revisions made by the other).

When the determination is to retrieve the decode threshold number of theother encoded data slices, the method continues at step 520 where theprocessing module retrieves the decode threshold number of the otherencoded data slices. The method continues at step 522 where theprocessing module decodes the decode threshold number of the otherencoded data slices to recover the data segment having the second statuslevel. Alternatively, or in addition to, the processing module decodesthe decode threshold number of the encoded data slices to recover thedata segment having the first status level. When the decode thresholdnumber of the other encoded data slices was retrieved based on the timeconcurrency of write requests of the data segment, the processing modulemay merge changes of the data segment having the second status levelindication into the data segment having the first status levelindication.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section(e.g., a non-transitory computer readable storage medium) that storesoperational instructions can, when executed by one or more processingmodules of one or more computing devices of the dispersed storagenetwork (DSN), cause the one or more computing devices to perform any orall of the method steps described above.

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the distributed storageand task (DST) client module 34 of FIG. 1, the network 24 of FIG. 1, anda storage set 530. The storage set 530 includes a set of DST execution(EX) units 1−n. Each DST execution unit may be implemented utilizing theDST execution unit 36 of FIG. 1. The DST client module 34 includes theoutbound DST processing 80 of FIG. 3, the memory 88 of FIG. 3, and theinbound DST processing 82 of FIG. 3. The DSN functions to capture datafor storage in the set of DST execution units, where the capturing ofthe data may include receiving one or more of a random writes and randomupdated writes for produce the received portions of the data. The datamay be received as at least one of a data object, a data file, and adata stream 532.

In an example of operation, the outbound DST processing 80 initiatesreceiving the data stream 532 for storage in the storage set 530. Theoutbound DST processing 80 dispersed storage error encodes a first dataportion of the data stream to produce a first slice grouping includesone or more sets of encoded data slices. Having produced the first slicegroup, the outbound DST processing 80 facilitates storing of the firstslice group in the storage set 530. For example, at time t1, theoutbound DST processing 80 sends, via the network 24, the first slicegroup to the set of DST execution units 1−n for storage.

Having facilitated storing of the first slice group, the outbound DSTprocessing 80 receives, prior to concluding receiving of the datastream, an update to a sub-portion of the first data portion. Forexample, the outbound DST processing 80 receives a random overwrite forthe previously received sub-portion of the first data portion.

For each set of the one or more sets of encoded data slices of the firstslice group, the inbound DST processing 82 recovers at least a decodethreshold number of encoded data slices. For example, the inbound DSTprocessing 82 issues read slice requests to the storage set and receivesencoded data slices of the first slice group. Having received theencoded data slices of the first slice group, the inbound DST processing82 dispersed storage error decodes the at least a decode thresholdnumber of received encoded data slices of each of the one or more setsof encoded data slices to reproduce the first data portion. The inboundDST processing 82 may store the recovered data portion 1 in the memory88.

The outbound DST processing 80 updates the recovered data portion 1 withthe updates to recovered data portion 1 to produce an updated dataportion 1. The updating may include one or more of overwriting data ofthe recovered data portion 1 with the update to the sub-portion,interleaving data of the recovered data portion 1 with the update to thesub-portion, inserting the update to the sub-portion into the recovereddata portion 1, and appending the update to the sub-portion to therecovered data portion 1 to produce the updated data portion 1.

Having produced the updated data portion 1, the outbound DST processing80 dispersed storage error encodes the updated data portion 1 to producean updated first slice group. Having produced the updated first slicegroup, the outbound DST processing 80 facilitates storing of the updatedfirst slice group in the storage set 530. For example, at a time framet2, the outbound DST processing 80 sends, via the network 24, theupdated slice group 1 to the set of DST execution units 1−n for storage.

When detecting conclusion of receiving of the data stream, the outboundDST processing 80 facilitates committing of the storage of the updatedfirst slice group. For example, at a time frame t3, the outbound DSTprocessing 80 sends, via the network 24, a commit transaction request tothe set of DST execution units 1−n, where the commit transaction requestincludes a transaction number associated with the storing of the updatedfirst slice group.

Alternatively, while receiving the first data portion, the outbound DSTprocessing 80 stores the first data portion in the memory 88. Theoutbound DST processing 80 stops storing the data in the memory 88 whenreceiving the update to the sub-portion. When detecting conclusion ofthe receiving of the data stream, the outbound DST processing 80dispersed storage error encodes the updated data portion from the memory88 for storage in the storage set.

Alternatively, when receiving the update to the sub-portion, the inboundDST processing 82 recovers a corresponding portion of the first dataportion from the storage set for modification using the update. Havingmodified the recovered corresponding portion of the first data portion,the outbound DST processing 80 dispersed storage error encodes themodified first data portion to produce updated encoded data slices andoverwrites previously stored encoded data slices and the storage setwith the updated encoded data slices.

FIG. 46B is a flowchart illustrating an example of updating captureddata in accordance the present invention. The method begins or continuesat step 534 where a processing module (e.g., of a distributed storageand task (DST) client module) initiates receiving a data stream forstorage in a set of storage units. The initiating may include one ormore of initiating a query, receiving a header, and receiving a largedata file. The method continues at step 536 where the processing moduledispersed storage error encodes a first data portion of the data streamto produce a first slice group, where the first slice group includes oneor more sets of encoded data slices.

The method continues at step 538 where the processing module facilitatesstorage of the first slice group in the set of storage units. The methodcontinues at step 540 where the processing module receives, prior toconcluding receiving of the data stream, an update to a sub-portion ofthe first data portion. For example, the processing module receives arandom write request with an indicator associated with the first dataportion and/or the sub-portion of the first data portion.

The method continues at step 542 where the processing module recovers atleast a decode threshold number of encoded data slices for each set ofencoded data slices of the first slice group from the set of storageunits. The method continues at step 544 where the processing moduledecodes the recovered encoded data slices to reproduce the first dataportion. For example, the processing module decodes a decode thresholdnumber of encoded data slices for each set of encoded data slices toreproduce the first data portion.

The method continues at step 546 where the processing module modifiesthe reproduced first data portion using the update to the sub-portion toproduce an updated first data portion. The modifying includes at leastone of replacing, overwriting, and appending the reproduced first dataportion with the update to the sub-portion to produce the updated firstdata portion. The method continues at step 548 where the processingmodule dispersed storage error encodes the updated first data portion toproduce an updated first slice group that includes an updated one ormore sets of encoded data slices.

The method continues at step 550 where the processing module facilitatesstorage of the updated first slice group in the set of storage units.When concluding the receiving of the data stream, the method continuesat step 552 where the processing module facilitates committing of thestorage of the updated for slice group. For example, the processingmodule detects an indicator that the data stream has been received andissues a set of commit transaction requests to the set of storage units,where the set of commit transaction request includes a transactionnumber associated with write slice requests of the storage of theupdated for slice group in the set of storage units.

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the outbound distributedstorage and task (DST) processing 80 of FIG. 3, the network 24 of FIG.1, and a storage set 560. The storage set 560 includes a set of DSTexecution (EX) units 1−n. Each DST execution unit may be implementedutilizing the DST execution unit 36 of FIG. 1. The outbound DSTprocessing 80 includes the data partition 110 of FIG. 4, a dispersedstorage (DS) error encoding 1, a dispersed storage (DS) error encoding2, and an auxiliary data generator module 562. The auxiliary datagenerator module 562 may be implemented utilizing the processing module84 of FIG. 3. The DS error encoding 1 and the DS error encoding 2 may beimplemented utilizing the DS error encoding 112 of FIG. 4. The DSNfunctions to store data 564 and associated auxiliary data 574 in thestorage set 560.

In an example of operation, the outbound DST processing 80 receives thedata 564 for storage. Having received the data 564 for storage, theauxiliary data generator module 562 processes one or more of the data564 and other data 572 to produce the auxiliary data 574. The other data572 may include one or more of a requesting entity identifier, a dataowner identifier, a timestamp, and an identifier associated with thedata. The processing includes one or more of counting bytes of the datato produce a data size indicator, performing a hashing function over thedata to produce a hash value, appending the other data, and analyzingthe data to produce a data type indicator.

The DS error encoding 2 dispersed storage error encodes the auxiliarydata 574 to produce auxiliary data slices 576. The outbound DSTprocessing 80 obtains a DSN address 566 for storage of the auxiliarydata. For example, the outbound DST processing 80 generates slice namesfor the auxiliary data slices based on the data identifier of the data.As another example, the outbound DST processing 80 generates slice namesfor the auxiliary data slices based on a random number.

The outbound DST processing 80 sends, via the network 24, the auxiliarydata slices 576 to the storage set 560 for storage using the DSN addressof the auxiliary data 566. For example, the outbound DST processing 80generates a set of write slice requests that includes the slice namesfor the auxiliary data slices and the auxiliary data slices 576, sends,via the network 24, the write slice requests to the set of DST executionunits 1−n.

The data partitioning 110 generates data partitions 120 to include aplurality of data segments from the data 564 and the DSN address of theauxiliary data 566, where at least one data segment includes the DSNaddress of the auxiliary data 566. For example, the data partition 110generates a first data segment to include the DSN address of theauxiliary data 566 and a first data portion to complete the first datasegment, and generates data segments 2-Y from remaining data portions ofthe data such that each data segment is substantially a same size.

The outbound DST processing 80 facilitates storage of the datapartitions 120 in the storage set. For example, for each data segment ofthe Y data segments, the DS error encoding 1 dispersed storage errorencodes the data segment to produce a set of encoded data slices of Ysets of encoded data slices 570. The outbound DST processing 80 sends,via the network 24, the Y sets of encoded data slices 570 to the storageset 560 for storage. For example, the outbound DST processing 80generates a set of write slice requests to include the Y sets of encodeddata slices, and sends, via the network 24, the set of write slicerequests to the set of DST execution units 1−n. When retrieving the data564, the first data segment is recovered, the DSN address of theauxiliary data is extracted from the first data segment, and theauxiliary data is recovered using the extracted DSN address of theauxiliary data.

FIG. 47B is a flowchart illustrating an example of associating storageof data and auxiliary data in a dispersed storage network in accordancethe present invention. The method begins or continues at step 578 wherea processing module (e.g., of an outbound distributed storage and task(DST) processing module) receives data for storage in a set of storageunits of a dispersed storage network (DSN) memory. The method continuesat step 580 where the processing module processes the data to produceauxiliary data. For example, the processing module analyzes the data toproduce the interim auxiliary data and integrates other data with theinterim auxiliary data to produce the auxiliary data.

The method continues at step 582 where the processing module obtains aDSN address for storage of the auxiliary data. For example, theprocessing module generates a new DSN address based on a vaultidentifier associated with storage of the data and a random number. Themethod continues at step 584 where the processing module facilitatestorage of the auxiliary data in the set of storage units using the DSNaddress for storage of the auxiliary data. For example, the processingmodule generates a set of slice names based on the DSN address forstorage of the auxiliary data, dispersed storage error encodes theauxiliary data to produce a set of encoded auxiliary data slices,generates a set of write slice requests to include the set of slicenames and the set of encoded auxiliary data slices, and sends the set ofwrite slice requests to the set of storage units.

The method continues at step 586 where the processing module generates aplurality of data segments from the data in the DSN address of theauxiliary data, where at least one data segment includes the DSN addressof the auxiliary data. For example, the processing module selects a datasegment for inclusion of the DSN address of the auxiliary data,partitions the data to produce the plurality of data segments for theselected data segment includes the DSN address of the auxiliary data,and where each data segment is substantially a same size.

The method continues at step 588 where the processing module facilitatesstorage of the plurality of data segments in the set of storage units.For example, for each data segment, the processing module dispersestorage error encodes the data segment to produce a set of encoded dataslices, and sends the set of encoded data slices to the set of storageunits.

FIG. 48A is a diagram of an embodiment of a backup file system structurethat includes a temporary report for a data file group, one or morebackup files, and a master index file. The backup file system structuremay be utilized to periodically, from time to time, produce a backuprecord of the data file group (e.g., archiving storage of a copy of atleast part of the data file group), where the data file group includes aplurality of affiliated data files. Such an affiliation may include oneor more of a family of DSN directory files, a family of dispersedhierarchical index files, a group of data files associated with aparticular user of a dispersed storage network, a group of data filesassociated with a particular group of users of the dispersed storagenetwork, etc.

Each data file is associated with a name of the data file. For example,at a time t0 data file group includes data file 1 with an associatedname of the data file 1, a data file 2 with an associated name of thedata file 2, and a data file 3 with an associated name of the data file3.

In an example of operation of an initial generation of the backup filesystem structure, at time t0, a processing module of a dispersed storagenetwork (DSN) generates a temporary report for the data file group. Thetemporary report includes each name of each data file and, for eachname, a corresponding hash value of the data file associated with thename. For example, the processing module performs a hashing function ondata file 1 to produce the hash of data file 1, and associates a hash ofthe data file 1 with the name of the data file 1.

Having produced the temporary report for the data file group, theprocessing module generates a first backup file, at time t0, byincluding each data file of the data file group and each associated hashvalue of each data file. For example, the processing module generatesthe backup file 1 to include the data file 1 and the associated hash ofdata file 1, the data file 2 and the associated hash of data file 2, andthe data file 3 and the associated hash of data file 3. Having producedthe backup file 1, the processing module facilitates storage of thebackup file 1 in a dispersed storage network memory. For example, theprocessing module dispersed storage error encodes the backup file 1 toproduce a plurality of sets of encoded backup file slices, sends theplurality of sets of encoded backup file slices to the DSN memory forstorage using a DSN address for storage of the backup file 1, andupdates a DSN directory to associate the DSN address for storage of thebackup file 1 with a name of the backup file 1.

Having generated the backup file 1, the processing module creates themaster index file at time t0. The processing module generates the masterindex file to include a series of entries where each entry includes aname of a data file, a name of the corresponding backup file thatincludes the data file associated with the name of the data file, andthe hash of the data file. For example, the processing module generatesa first entry of the master index file to include the name of the datafile 1, the name of the backup file 1, and the hash of the data file 1;generates a second entry of the master index file to include the name ofthe data file 2, the name of the backup file 1, and the hash of the datafile 2; and generates a third entry of the master index file to includethe name of the data file 3, the name of the backup file 1, and the hashof the data file 3.

Having generated the master index file, the processing modulefacilitates storage of the master index file in the DSN memory. Forexample, the processing module dispersed storage error encodes themaster index file to produce at least one set of encoded index fileslices and sends the at least one set of encoded index file slices tothe DSN memory for storage using a DSN address associated with themaster index file (e.g., a predetermined DSN address).

In an example of operation of updating of the backup file systemstructure, at time t1, the processing module generates an updatedtemporary report for the data file group. For example, the processingmodule performs the hashing function on a newly updated data file 2 toproduce a new hash of new data file 2 and creates a first entry toinclude the new hash of new data file 2 and the name of data file 2;performs the hashing function on the data file 3 to produce a hash ofdata file 3 and creates a second entry to include the hash of data file3 and the name of data file 3; and performs the hashing function on adata file 4 to produce a hash of data file 4 and creates a third entryto include the hash of data file 4 and the name of data file 4 when,between time t0 and t1, data file 1 has been removed from the data filegroup, a data file 2 has been updated, data file 3 remains, and datafile 4 has been added to the data file group.

Having produced the updated temporary report for the data file group,the processing module generates a second backup file, at time t1, bygenerating an entry for each newly added data file and each updated datafile. For example, the processing module generates the backup file 2 toinclude a first entry that includes the new hash of data file 2 and thenew data file 2; and the hash of data file 4 and the data file 4. Havingproduced the backup file 2, the processing module facilitates storage ofthe backup file 2 in the DSN memory. For example, the processing moduledispersed storage error encodes the backup file 2 to produce anotherplurality of sets of encoded backup file slices, sends the otherplurality of sets of encoded backup file slices to the DSN memory forstorage using another DSN address for storage of the backup file 2, andupdates a DSN directory to associate the DSN address for storage of thebackup file 2 with a name of the backup file 2.

Having generated the backup file 2, the processing module updates themaster index file at time t1. The processing module recovers the masterindex file from the DSN memory and updates the recovered master indexfile to produce an updated master index file. The processing moduleupdates the master index file to include an entry corresponding to eachdata file that currently belongs to the data file group. For example,the processing module updates the master index file to include a firstentry that includes the name of the data file 2, the name of the backupfile 2, and the new hash of the data file 2; maintains a second entry ofthe master index file to include the name of the data file 3, the nameof the backup file 1, and the hash of the data file 3; generates a newthird entry of the master index file to include the name of the datafile 4, the name of the backup file 2, and the hash of the data file 4.

Having generated the updated master index file, the processing modulefacilitates storage of the updated master index file in the DSN memoryusing the DSN address associated with the master index file. Forexample, the processing module dispersed storage error encodes theupdated master index file to produce at least one set of updated encodedindex file slices and sends the at least one set of updated encodedindex file slices to the DSN memory for storage using the DSN addressassociated with the master index file.

The processing module may restore a corrupted or missing data file ofthe data file group by accessing the master index file from the DSNmemory and accessing and associated backup file to recover the datafile. Alternatively, or in addition to, the processing module may deletea backup file when each data file is no longer required. For example,the processing module deletes file 1 when data file 3 is no longerrequired (e.g., since data file 1 has already been removed from the datafile group and data file 2 has been modified).

FIG. 48B is a flowchart illustrating an example of performing anefficient backup of a group of data files using a dispersed storagenetwork in accordance the present invention. The method begins orcontinues at step 590 where a processing module (e.g., of a distributedstorage and task (DST) client module), for each data file of the datafile group, performs a hashing function on the data file to produce ahash value of the data file where each data file has a name of the datafile. For example, the processing module searches a data file group toidentify each data file and data file name. For instance, the processingmodule searches a dispersed storage network directory. As anotherexample, the processing module searches a dispersed hierarchical indexto obtain each node file of the index. Alternatively, the processingmodule performs an integrity function on the data file to produce anintegrity check value. The integrity function includes at least one of adeterministic function, a hash-based message authentication codefunction, a mask generating function, a cyclic redundancy checkfunction, and a sponge function.

The method continues at step 592 where the processing module recovers abackup record from a dispersed storage network (DSN) memory, where thebackup record includes a name of a backed up data file, a name of abackup file that includes a backed up data file, and a hash value of thebacked up data file. For example, the processing module obtains a DSNaddress for the backup record (e.g., based on a lookup, based onaccessing the dispersed hierarchical index, based on accessing adirectory, based on accessing a portion of the system registry), issuesa set of read slice requests to the DSN memory using the DSN address forthe backup record, receives at least a decode threshold number ofencoded backup record slices, and dispersed storage error decodes thedecode threshold number of encoded backup record slices to reproduce thebackup record.

The method continues at step 594 where, for each pairing of name of thedata file and the corresponding hash value, the processing moduledetermines whether a similar pairing exists for a previous backup basedon the backup record. For example, the processing module indicates thata new version of a data file exists when a data file name matches but adata file hash does not. As another example, the processing moduleindicates a new data file when a data file name of the data file groupdoes not match any data file name of the backup record. As yet anotherexample, the processing module indicates no changes to an existing filewhen a pairing matches.

For each pairing without a similar pairing of the previous backup, themethod continues at step 596 where the processing module generates a newbackup file to include the data file in the corresponding hash value.For example, the processing module generates the new backup file toinclude the data file and the corresponding hash value for each modifiedor new data file. The method continues at step 598 where the processingmodule facilitates storage of the new backup file in the DSN memory. Forexample, the processing module encodes the new backup file to produce aset of encoded backup file slices, obtains a name of the new backupfile, generates a set of slice names based on the name of the new backupfile, and issues read slice requests to the DSN memory, where the writeslice requests includes the set of slice names and the set of encodedbackup file slices.

The method continues at step 600 where the processing module updates thebackup record to include the pairing without the similar pairing of theprevious backup in the name of the new backup file. For example, theprocessing module includes the non-matching hash value, the name of thecorresponding data file, in the name of the new backup file. Theprocessing module stores the updated backup record in the DSN memory.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.,described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc., that mayuse the same or different reference numbers and, as such, the functions,steps, modules, etc., may be the same or similar functions, steps,modules, etc., or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a computing device of adispersed storage network (DSN), the method comprises: identifying adata object for retrieval from DSN memory, wherein the data object isstored as a plurality of sets of encoded data slices in a set of storageunits of the DSN, wherein the data object is dispersed storage errorencoded with first encoding parameters to produce the plurality of setsof encoded data slices; determining whether an access metric regardingthe data object exceeds an access threshold, wherein, when the accessmetric is equal to or exceeds the access threshold, the data object isfurther stored as a second plurality of sets of encoded data slices in asecond set of storage units of the DSN, wherein the data object isfurther dispersed storage error encoded with second encoding parametersto produce the second plurality of sets of encoded data slices, andwherein a first decode threshold and a first pillar width of the firstencoding parameters are greater than a second decode threshold and asecond pillar width of the second encoding parameters; when the accessmetric exceeds the access threshold: issuing a plurality of sets ofretrieval requests to the second set of storage units regarding thesecond plurality of encoded data slices in accordance with a readthreshold of the second encoding parameters; and recovering the dataobject from received encoded data slices of the second plurality ofencoded data slices.
 2. The method of claim 1 further comprises: whenthe access metric is less than the access threshold: issuing a firstplurality of sets of retrieval requests to the set of storage unitsregarding the first plurality of encoded data slices in accordance witha read threshold of the first encoding parameters; and recovering thedata object from received encoded data slices of the first plurality ofencoded data slices.
 3. The method of claim 1, wherein the access metriccomprises one or more of: network traffic loading information; accessrate of the data object; and storage unit loading of a set of storageunits storing the first plurality of sets of encoded data slices.
 4. Themethod of claim 1 further comprises: the second decode threshold numberis less than or equal to one-half of the first decode threshold number.5. The method of claim 1 further comprises: the second decode thresholdnumber is less than or equal to one-half of a total number of encodeddata slices in a set of the second plurality of sets of encoded dataslices.
 6. The method of claim 1, wherein the recovering the data objectfrom received encoded data slices of the second plurality of encodeddata slices comprises: for a first data segment of the data object:receiving the second decode threshold number of encoded data slices of afirst set of encoded data slices of the second plurality of sets ofencoded data slices; and dispersed storage error decoding the seconddecode threshold number of encoded data slices of the first set torecover the first data segment; for a second data segment of the dataobject: receiving the second decode threshold number of encoded dataslices of a second set of encoded data slices of the second plurality ofsets of encoded data slices; and dispersed storage error decoding thesecond decode threshold number of encoded data slices of the second setto recover the first data segment; and combining the first and seconddata segments to produce at least a portion of the data object.
 7. Acomputer readable memory comprises: at least one memory section thatstores operational instructions that, when executed by a computingdevice of a dispersed storage network (DSN), causes the computing deviceto: identify a data object for retrieval from DSN memory, wherein thedata object is stored as a plurality of sets of encoded data slices in aset of storage units of the DSN, wherein the data object is dispersedstorage error encoded with first encoding parameters to produce theplurality of sets of encoded data slices; determine whether an accessmetric regarding the data object exceeds an access threshold, wherein,when the access metric is equal to or exceeds the access threshold, thedata object is further stored as a second plurality of sets of encodeddata slices in a second set of storage units of the DSN, wherein thedata object is further dispersed storage error encoded with secondencoding parameters to produce the second plurality of sets of encodeddata slices, and wherein a first decode threshold and a first pillarwidth of the first encoding parameters are greater than a second decodethreshold and a second pillar width of the second encoding parameters;when the access metric exceeds the access threshold: issue a pluralityof sets of retrieval requests to the second set of storage unitsregarding the second plurality of encoded data slices in accordance witha read threshold of the second encoding parameters; and recover the dataobject from received encoded data slices of the second plurality ofencoded data slices.
 8. The computer readable memory of claim 7, whereinthe at least one memory section further stores operational instructionsthat, when executed by the computing device, causes the computing deviceto: when the access metric is less than the access threshold: issue afirst plurality of sets of retrieval requests to the set of storageunits regarding the first plurality of encoded data slices in accordancewith a read threshold of the first encoding parameters; and recover thedata object from received encoded data slices of the first plurality ofencoded data slices.
 9. The computer readable memory of claim 7, whereinthe access metric comprises one or more of: network traffic loadinginformation; access rate of the data object; and storage unit loading ofa set of storage units storing the first plurality of sets of encodeddata slices.
 10. The computer readable memory of claim 7 furthercomprises: the second decode threshold number is less than or equal toone-half of the first decode threshold number.
 11. The computer readablememory of claim 7 further comprises: the second decode threshold numberis less than or equal to one-half of a total number of encoded dataslices in a set of the second plurality of sets of encoded data slices.12. The computer readable memory of claim 7, wherein the at least onememory section further stores operational instructions that, whenexecuted by the computing device, causes the computing device to recoverthe data object from received encoded data slices of the secondplurality of encoded data slices by: for a first data segment of thedata object: receiving the second decode threshold number of encodeddata slices of a first set of encoded data slices of the secondplurality of sets of encoded data slices; and dispersed storage errordecoding the second decode threshold number of encoded data slices ofthe first set to recover the first data segment; for a second datasegment of the data object: receiving the second decode threshold numberof encoded data slices of a second set of encoded data slices of thesecond plurality of sets of encoded data slices; and dispersed storageerror decoding the second decode threshold number of encoded data slicesof the second set to recover the first data segment; and combining thefirst and second data segments to produce at least a portion of the dataobject.
 13. A computing device of a dispersed storage network (DSN), thecomputing device comprises: an interface; a local memory; and aprocessing module operably coupled to the interface and the localmemory, wherein the processing module functions to: identify a dataobject for retrieval from DSN memory, wherein the data object is storedas a plurality of sets of encoded data slices in a set of storage unitsof the DSN, wherein the data object is dispersed storage error encodedwith first encoding parameters to produce the plurality of sets ofencoded data slices; determine whether an access metric regarding thedata object exceeds an access threshold, wherein, when the access metricis equal to or exceeds the access threshold, the data object is furtherstored as a second plurality of sets of encoded data slices in a secondset of storage units of the DSN, wherein the data object is furtherdispersed storage error encoded with second encoding parameters toproduce the second plurality of sets of encoded data slices, and whereina first decode threshold and a first pillar width of the first encodingparameters are greater than a second decode threshold and a secondpillar width of the second encoding parameters; when the access metricexceeds the access threshold: issue, via the interface, a plurality ofsets of retrieval requests to the second set of storage units regardingthe second plurality of encoded data slices in accordance with a readthreshold of the second encoding parameters; and recover the data objectfrom received encoded data slices of the second plurality of encodeddata slices.
 14. The computing device of claim 13, wherein theprocessing module is further operable to: when the access metric is lessthan the access threshold: issue, via the interface, a first pluralityof sets of retrieval requests to the set of storage units regarding thefirst plurality of encoded data slices in accordance with a readthreshold of the first encoding parameters; and recover the data objectfrom received encoded data slices of the first plurality of encoded dataslices.
 15. The computing device of claim 13, wherein the access metriccomprises one or more of: network traffic loading information; accessrate of the data object; and storage unit loading of a set of storageunits storing the first plurality of sets of encoded data slices. 16.The computing device of claim 13 further comprises: the second decodethreshold number is less than or equal to one-half of the first decodethreshold number.
 17. The computing device of claim 13 furthercomprises: the second decode threshold number is less than or equal toone-half of a total number of encoded data slices in a set of the secondplurality of sets of encoded data slices.
 18. The computing device ofclaim 13, wherein the processing module further functions to recover thedata object from received encoded data slices of the second plurality ofencoded data slices by: for a first data segment of the data object:receiving, via the interface, the second decode threshold number ofencoded data slices of a first set of encoded data slices of the secondplurality of sets of encoded data slices; and dispersed storage errordecoding the second decode threshold number of encoded data slices ofthe first set to recover the first data segment; for a second datasegment of the data object: receiving, via the interface, the seconddecode threshold number of encoded data slices of a second set ofencoded data slices of the second plurality of sets of encoded dataslices; and dispersed storage error decoding the second decode thresholdnumber of encoded data slices of the second set to recover the firstdata segment; and combining the first and second data segments toproduce at least a portion of the data object.